Economics is Broken

There’s a reason we place more value on astronomy than we do on astrology. Your astrologer can tell you that maybe, perhaps, this is a good day to do something very vague like “start a new venture,” or “explore romantic options.” Your astronomer, on the other hand, can so precisely calculate the speed and location of an object hurtling through space that engineers can successfully land a delicate robot on it.

If astrology was as useful as astronomy, your chart would not just advise you to “be open to a relationship,” it would include a name, email address, Facebook profile, specify your future wedding date, and describe your great-grandkids’ favorite hobbies. We trust science because it works.

That’s why economics has developed into such a monumental disappointment. It claims the authority of a science, but it doesn’t work. It’s time to send it back to the lab.

In fairness, the social sciences are hobbled by a problem that physicists and astronomers don’t face. The uncertainty that frustrates physicists at the quantum level is a day to day reality for economists at every level. They work to define, understand, and manipulate a broad series of interconnected systems which are actually growing more complex while they are observed.

Consider those NASA scientists and engineers that landed a rover on Mars. How much more difficult would their task have been if the solar system was prone to spew out or destroy new moons or planets on a whim on any given Thursday afternoon? The physical laws of the universe are not changing. Economists are studying systems which are alive; driven by human values and gaining in complexity by the moment.

To cope with this complexity and dynamism, economists build simplified theoretical models. Those models can be very useful in understanding broad-stroke concepts, like the manner in which money supply can influence inflation, or how supply and demand interact to set prices. However, because of their assumptions and simplifications, those models cannot deliver the precision of a science. Economists of recent generations have been reluctant to fully acknowledge those limitations, (see Krugman, Paul).

Instead they build ever more precise mathematical equations atop their flawed models. The math is reliable; at least so much as it can predict an outcome in the real world that perfectly matches the assumptions in their models. But nothing in the real world ever matches the simplifications of their models.

Economics in our time is a philosophy dressed up in equations. That does not imply that economics is worthless, only that is should not be trusted to deliver precision or provable certainty.

“I think one of the great errors we as economists made was that we started believing the assumptions of economics, and saying things that made no intellectual sense. We started to believe that what were assumptions were actually a description of reality, and therefore that the models were a description of reality, and therefore were dependable for policy analysis.

“With hindsight, that was a pretty significant error.”

Political theorists, by contrast, are able to make real, meaningful contributions without claiming any empirical authority. And their insights are getting better, as demonstrated in the recent book, Why Nations Fail.

Popular investment writers like Barry Ritholtz at The Big Picture blog are carving holes in traditional, street-level economic assumptions. Business thinkers like Eric Beinhocker are demonstrating the practical implications of complexity. Umair Haque is exploring a fresh understanding of capitalism that incorporates a more realistic set of assumptions about human needs in a marketplace. There is reason to hope that economics might one day offer advice that works.

In the meantime, we should trust economics in the same manner that we trust philosophy. Economics in our time cannot predict outcomes, but like political science, it can help us build policies that reflect our values. Economics can inform political decisions, but it cannot replace them.

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Tim Harford’s TED talk on uncertainty and complexity in decision-making: